Device to detect and treat apneas and hypopnea

ABSTRACT

A method and apparatus for the treatment of Sleep Apnea events and Hypopnea episodes wherein one embodiment comprises a wearable, belt like apparatus containing a microphone and a plethysmograph. The microphone and plethysmograph generate signals that are representative of physiological aspects of respiration, and the signals are transferred to an imbedded computer. The embedded computer extracts the sound of breathing and the sound of the heart beat by Digital Signal Processing techniques. The embedded computer has elements for determining when respiration parameters falls out of defined boundaries for said respiration parameters. This exemplary method provides real-time detection of the onset of a Sleep Apnea event or Hypopnea episode and supplies stimulation signals upon the determination of a Sleep Apnea event or Hypopnea episode to initiate an inhalation. In one embodiment, the stimulus is applied to the patient by a cutaneous rumble effects actuator and/or audio effects broadcasting.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation to U.S. patent application Ser. No. 17/403,661, filed Aug. 16, 2021, which is a Continuation of U.S. patent application Ser. No. 15/963,709, filed Apr. 26, 2018 (now U.S. Pat. No. 11,089,994), which is a Continuation of U.S. Patent application Ser. No. 12/277,386, filed Nov. 25, 2008, which claims the benefit of U.S. Provisional Application No. 60/990,035, filed Nov. 26, 2007, each of which are incorporated herein by reference in their entireties.

TECHNICAL FIELD

The present invention relates to an apparatus to detect and end occurrences of Sleep Apnea event and Hypopnea episode, in a manner that will decrease or eliminate hypoxia, hypercapnia and the disturbance of pulmonary hemodynamics.

Background

Sleep disordered breathing (SDB) is a group of breathing disorders that occur during periods of sleep. The most serious forms of sleep disordered breathing involve an intermittent cessation (apnea) or reduction (hypopnea) of ventilation during sleep that results in physiologic disturbances including a decrease in blood oxygen levels (hypoxia), increase in CO2 (hypercapnia), and autonomic activation resulting in vasoconstriction. The long term effects of these physiological changes are associated with the development of cardiac arrhythmias, congestive heart failure, cardiac ischemia, hypertension, heart disease, brain damage, and diabetes. Another form of sleep disordered breathing is respiratory effort-related arousals (RERA) defined as “obstructed events that do not meet the criteria for apnea or hypopnea but that nevertheless cause an arousal. More specifically, RERA are defined as the absence of apnea/hypopnea but with progressive negative Pes (esophageal pressure) lasting about 10 seconds culminating in an arousal.” (Halasz et al, 2004).

The causes of the various forms of sleep apnea and hypopnea are not fully understood.

There are three general types of sleep apnea: obstructive sleep apnea (OSA), central sleep apnea (CSA), and mixed sleep apnea. Obstructive sleep apnea (the most common type) is characterized by a blockage or occlusion of the oropharyngeal (upper) airway due to a loss of patency of its muscles. With obstructive sleep apnea, respiratory effort continues and may be apparent as paradoxical movement of the thorax or abdomen. This paradoxical movement acts as a one way piston: air leaves the lungs but little or none can enter. The cause or causes of Obstructive Sleep Apneas is still a matter of much debate and research.

The average Apnea event lasts 20 seconds, however events of 2 to 3 minutes are not unknown. During the event, a number of physiological events occur. These include a vagal bradycardia, an increase in blood pressure, an increase in norepinephrine, and paradoxical respiratory efforts with increased respiratory effort. As an apnea event progresses, there is an increasing effort to breathe, increasing carbon dioxide (hypercapnia), decreasing oxygen, and increasing level of proprioception. The longer the Apnea event, the more extreme these changes are.

At the end of an Apnea event tone returns to the upper airway muscles so that the upper airway suddenly re-opens (restoration of patency). This can be associated with a sudden gasp or choking as air rapidly enters the lungs, and with surges in heart rate and blood pressure.

It has been believed that an arousal from a deeper stage of sleep to a lighter stage of sleep was required to terminate an Apnea episode; however studies have cast doubt on that assertion. “[During sleep] the brain is permanently active and is able to control the autonomic, metabolic and hormonal changes that take place within the body and simultaneously determine the behavioral responses to the external stimuli. Although sleep is characterized by decreased conscious perception, these tasks are accomplished nevertheless during sleep through a gradual activation of the brain or through a partial activation confined to some cerebral areas (Ujszaszi and Halasz 1988) . . . . In this way, the sleeping brain not only regulates the reactions but also assimilates in its functions the incoming information. From a functional point of view, sleep modulates and is modulated by this series of interactions.” (Halasz et al, 2004)

“Compared with wakefulness, sleep is subjectively perceived as a reduced responsiveness to environmental stimuli induced by a selective closure to the inputs arriving from the external world (Steriade 2000a). The filter that gates the flux of information from the peripheral receptors to the cortex is situated in the thalamocortical connections where the incoming signals are blocked or attenuated via synaptic inhibition. This mechanism modulates the susceptibility of the cerebral cortex to all the activating stimuli. In particular, the generators of cortical electrical activity are modified during sleep and shift from the production of low amplitude high-frequency electroencephalographic (EEG) activity (LAHF mode) typical expression of the massive activation of the cortical cells, to the production of high amplitude low-frequency EEG activity (HALF mode) indicating a widespread synchronization of the cortical cells (Steriade and Llinas 1988; Steriade and McCarley 1990; Steriade et al. 1990). Rapid eye movement (REM) sleep, which appears later in the night, is characterized by the simultaneous occurrence of LAHF EEG activity, absence of muscle tone and recurrent rapid eye movements . . . .

Attention to the functions and importance of activated brain states was first raised by Moruzzi and Magoun (1949) who demonstrated an ‘activation’ process in the changes of EEG waves and verified their brainstem origin. The discovery and localization of brainstem reticular arousal system (RAS) was made by lesion experiments and by electrical stimulation of the brainstem reticular core (Hobson 1978). The EEG effect of arousal was called as ‘desynchronization’, but the coincidence of desynchronization with the concept of arousal has created severe limitations to the future development of the field. Although slow synchronization thalamic devices are really decoupled and the EEG activity is flattened, a fast (30-40 Hz) EEG pattern synchronization appears in the cortical and thalamic networks (Steriade 1995). Accordingly, the term ‘desynchronization’ should be considered as a rapid shift from HALF, typical of sleep, to LAHF, typical of wakefulness.” (Halasz et al, 2004)

“The concept of ‘arousal’ has a long history, which is closely connected with the development of concepts about the neurophysiology of sleep and wakefulness. The criteria and measure of ‘arousal’ are controversial issues; hence, ‘arousal’ has several definitions (Halasz et al. 1979; Lofaso et al. 1998; Martin et al. 1997a; Rees et al. 1995; Schieber et al. 1971; Terzano et al. 1985) and several EEG, behavioral and autonomic aspects.” (Halasz et al, 2004)

An “EEG arousal,” “cortical arousal,” or “ASDA arousal” is defined as follows: “The American Sleep Disorders Association (ASDA) produced a consensus report (Atlas Task Force 1992) on the criteria of arousals in sleep in the early 1990s. [ASDA] arousal is defined as a rapid modification in [delta] EEG frequency, which can include theta and alpha activity, and/or frequencies higher than 16 Hz but not spindles. It can be accompanied by an increase of electromyographic activity, of cardiac frequency or by body movements. An [ASDA] arousal must be preceded by at least 10 s of continuous sleep land must last at least 3 seconds] . . . . The conventional [ASDA] definition of arousal includes a cluster of physiologic manifestations expressed by an activation of electrocorticographic rhythms, an increase of blood pressure and muscle tone and a variation of heart rate . . . . [ASDA] arousal, by definition, means cortical activation.” 2 (Halasz et al, 2004)

Changes in rhythm observed on EEG do not necessarily represent conventional cortical [ASDA] arousals. “Micro-Arousals (MA),” also known as “Transient activations” or “phases d′activation transitoire” (PAT) were originally defined as brief “phasic EEG events which were not associated with awakenings regardless of their desynchronizational or synchronizational (sleep response-like) morphology and regardless of their connection with autonomic or some sort of behavioral arousal . . . . The criteria for MA in NREM sleep given by Schieber et al. (1971) were the following: increase in EEG frequencies in conjunction with decrease of amplitudes, disappearance of delta waves and spindles, transitory enhancement of muscle tone or phasic appearance of groups of muscle potentials, movements of the limbs or changes in body posture, transitory rise in heart rate. In REM sleep the criteria for MAs were temporary disappearance of eye movements and appearance of alpha activities. The duration of these changes varied from some seconds to more than 10 s. Temporary activation is followed by deactivation leading to a bi-phasic character of the phenomenon.” (Halasz et al 2004) Under ASDA criteria (mASDA), transient increases in frequency lasting less than 3 seconds are classified as microarousals rather than cortical arousals.

Many other types of ‘arousals’ have been defined in the sleep literature. “Any behavioral expression, which occurs associated with low-voltage fast-EEG activities, is classified as a ‘behavioral arousal’ (Moruzzi and Magoun 1949) Similar features are shown by ‘movement arousals’ described as any increase in electromyographic activity that is accompanied by a change in any other EEG channel (Rechtschaffen and Kales 1968). When the EEG compartment is involved by transient desynchronization patterns [as specified in the ASDA criteria], regardless of the participation of the autonomic system or behavioral components, it was held as ‘cortical arousal’ (Atlas Task Force 1992). When there is evidence of vegetative or behavioral activation associated with an EEG pattern different from conventional [ASDA] arousal the event was defined as ‘subcortical arousal’ (McNamara et al. 2002; Rees et al. 1995). When an autonomic activation appears isolated or in conjunction with a respiratory event, but without any concomitant EEG sign, it is commonly defined as an ‘autonomic arousal’ (Martin et al. 1997b; Pitson and Stradling 1998). There is an autonomic ‘overarousal’ compared with the periods of arousal from continuous awake state during periods of awakening from NREM sleep (Homer et al. 1997), that also represents a certain kind of quantitative decoupling between the autonomic and other components of arousal.” (Halasz et al 2004)

The term “subcortical arousal” therefore does not imply that no areas of the cerebral cortex are active, but rather means an activation event during which the observed EEG pattern differs from the ASDA-specified pattern that defines a ‘cortical arousal’ (‘EEG arousal’). By definition a ‘subcortical arousal’ is not associated with a change of ASDA sleep stage classification, else it would meet the ASDA criteria for a ‘cortical arousal’. Although they may not be classified as ‘EEG arousals’ (cortical arousals), movement and behavioral arousals always involve some degree of EEG or autonomic activation: “movement and behavioral arousals without either EEG or autonomic concomitants do not exist.” (Halasz et al, 2004)

1 A particular EEG ‘cyclic alternating pattern’ (CAP) is “recognized as a physiologic component of normal NREM sleep (Bruni et al. 2002; Lofaso et al. 1998; Parrino et al. 1998; Terzano and Parrino 2000)” and defined as “different EEG features endowed with activating properties and coalesced into a common ‘brain beat’ (Terzano et al. 1985). In the CAP framework, ‘arousals’ are viewed as complex phenomena involving not only cortical areas but also other brain centers and peripheral neural components. These components are involved with different latencies and intensities but are nevertheless transformed into a unitary phenomenon by the reciprocal interneural connections (Moruzzi 1972). The activating phenomena occurring within the somato-vegetative systems do not always correspond to a cortical activation.” (Halasz et al, 2004) The cyclic alternation of CAP is divided in two major phases. “The CAP A-phase behaves like the synchronization arousals, can be elicited by sensory stimuli and is associated with clearly detectable autonomic discharges. Later the Parma school differentiated within the CAP A-phase three subtypes. In subtype A1, EEG synchrony is the predominant activity. If present, EEG desynchrony occupies less than 20% of the entire phase A duration. Subtype A1 is generally associated with mild autonomic and muscle activity. Subtype A2 contains a mixture of slow and rapid rhythms with 20-50% of phase A occupied by EEG desynchrony. Subtype A2 is linked with a moderate increase of muscle tone and/or cardiorespiratory rate. In subtype A3, the EEG activity is predominantly fast low voltage rhythms with greater than 50% of phase A occupied by EEG desynchrony. Subtype A3 is coupled with a remarkable activation of muscle tone and/or autonomic activities (Terzano et al. 2001).” In contrast, “phase B of CAP is closely related to the repetitive respiratory events of sleep-disordered breathing (Parrino et al. 2000a; Terzano et al. 1996; Thomas 2002), and only the powerful autonomic activation during the following CAP-A phase can restore post apnea breathing (Parrino et al. 2000b; Terzano et al. 1996) . . . . During sleep, an acoustic stimulus delivered during stable non-CAP can evoke a prolonged CAP sequence (Terzano and Parrino 1991).” (Halasz et al, 2004)

Arousals of all types may arise spontaneously: “Spontaneous arousals are natural guests of the sleeping brain (Boselli et al. 1998) and appear regularly embedded within the CAP process (Parrino et al. 2001; Terzano et al. 2002). However, arousal phenomena are also known to occur in response to sleep-disturbing factors. Increased amounts of arousals are a regular finding of obstructive sleep apnea syndrome (OSAS), but typical manifestations of secondary cortical events are also the ‘respiratory effort-related arousals’ (RERA) known as obstructed events that do not meet the criteria for apnea or hypopnea but that nevertheless cause an arousal. More specifically, RERA are defined as the absence of apnea/hypopnea but with progressive negative esophageal pressure lasting approximately 10 s culminating in an arousal. RERA are increased both in OSAS and in the ‘upper airway resistance syndrome’ (UARS) as a reaction of the sleeping brain to a repetitive breathing disturbance. RERA are secondary to subtle obstructions of the upper airway during sleep and can appear in the absence of apneas and hypopneas, causing excessive daytime sleepiness. The common abundance of RERA in sleep-disordered breathing (SDB) has supported the idea that arousals are a sign of disturbed sleep and that arousal responses reflect abnormal breathing (Douglas 2000).” (Halasz et a12004)

Cortical (ASDA, EEG) arousal is not necessary for termination of obstructive apnea or upper airway resistance syndrome events. “Some obstructive events terminate without obvious cortical [ASDA] arousal.” (Halasz et al 2004)

“Black et al. (2000) and Poyares et al. (2002) have found that airway opening may occur in UARS subjects with a predominant increase [rather than a decrease] in delta power. In other words, reopening of the airway at wakefulness and disappearance of abnormal UARS are not necessarily associated with an [ASDA] arousal. Reopening of the airway with an EEG pattern of delta has been also observed in OSAS patients (Berry et al. 1998). Involvement of either slow or fast EEG responses depends on the regulation of upper airway pathway. Respiratory patterns that need correction activate the CNS. This activation varies, depending on the sensory recruitment and the adequacy of the response. A respiratory challenge can be resolved by CNS activation without involving a cortical [ASDA] arousal.”

“In the vast majority of patients, if not in all patients, [ASDA] arousal is required neither to initiate UA (Upper Airway) opening nor to obtain adequate flow. UA opening would occur at approximately the same time regardless of when or whether arousal occurs and the flow response in most patients would still be timely and adequate. Arousals are incidental events that occur when the thresholds for arousal and arousal-independent opening are close to each other, as they appear to be in patients with OSA. By promoting an unnecessarily high flow response at UA opening, arousals help perpetuate cycling and likely exacerbate OSA.” (YOUNES, Magdy. Role of Arousals in the Pathogenesis of Obstructive Sleep Apnea. American Journal of Respiratory and Critical Care Medicine: Mar. 1, 2004, which is hereby incorporated by reference).

“Definition of Arousals and their Onset (T/AROUSAL). A more detailed account of Definition of Arousals and their Onset (T/AROUSAL) is given in the online supplement. A combination of EEG inspection and Fourier analysis was used. First, three EEG leads were inspected for a high-frequency shift greater than 3 seconds. If so, T/AROUSAL was the earliest point where the change occurred in any lead. A central EEG lead was analyzed by discrete Fourier transform in 3-second, nonoverlapping epochs spanning baseline (20 epochs) and dial-down. EEG power in the delta, theta, alpha, sigma, and beta ranges was computed. Confidence interval of 95% in baseline epochs was calculated for each frequency band. An arousal was deemed present at Tflow if a visible arousal that meets conventional criteria (Arousals EEG. Scoring rules and examples: a preliminary report from the sleep disorders atlas task force of the American sleep disorders association. Sleep 1992; 15:174-184) was present or if total high-frequency power (7.3-35.0 Hz) in the Tflow epoch was greater than the upper bound of the 95% confidence interval . . . .

Several previous reports noted the occurrence of UA opening without overt arousal (2-8). A number of explanations were proposed that would still be consistent with arousal-mediated opening (see Berry and coworkers [4] for review). What follows is a discussion of these possibilities and how they were addressed in this study.

1. An increase in EEG high frequency may be present but is equivocal or it lasts less than 3 seconds. This was addressed by comparing EEG power spectrum at UA opening with 20 baseline epochs. Arousal was called when high frequency content was significantly higher than baseline even if the change did not meet conventional criteria. This analysis would detect arousals even if the increase in high frequency involved a fraction of the epoch, so long as the change is outside the range observed in baseline.

2. Arousal may take the form of an increase in slow wave activity. Some investigators noted an increase in delta power near the end of obstructive events (8, 38). The significance of this phenomenon is unknown. Some believe it is an early or mild form of arousal (see Sforza and coworkers for a review). Others believe it represents accelerated progression to deep sleep in sleep-deprived patients (38). An increase in delta was found in 30% of observations classified as type 1 or 2 (see Table E1 in the online supplement). There was, however, no difference in flow response whether such changes were present or not (see FIG. E7A in the online supplement). Thus, even if delta increases are considered as arousals, they cannot be responsible for UA opening.

3. Arousals may be present without any cortical changes (subcortical or autonomic arousals). This possibility was excluded by demonstrating that heart rate was not higher at UA opening (in fact it was lower) than in the preceding breaths. The evidence for subcortical arousals stems from observations that external stimuli (e.g., acoustic) can increase heart rate and blood pressure even without cortical arousals (40, 41). Although heart rate and blood pressure responses to external stimuli may vary in individual subjects, the average responses invariably involve an increase in both variables (41-44). Thus, lack of an average increase in heart rate at UA opening in types 1 and 2 effectively rules out autonomic arousals at UA opening (an increase in blood pressure may still occur at UA opening, however, because of the increase in intrathoracic pressure [decreased cardiac afterload] and reduction in pulmonary vascular resistance as a result of improvement in alveolar gas tensions). Because respiratory muscle responses with subcortical arousals are considerably less than the autonomic response (compare ventilatory response to subcortical arousal in Badr and coworkers with autonomic response in the same subjects in Morgan and coworkers [41]), lack of an autonomic response makes it extremely unlikely that UA opening in these cases was produced by subcortical arousals. Two observations from this study further support this conclusion:

First, flow response in Breath 1 was similar whether cortical arousal was imminent (arousal in Breath 2) or not (FIG. 7 ). To the extent that activity in subcortical mechanisms must have been higher when arousal was imminent, this lack of difference suggests that subcortical arousal mechanisms do not exert an important effect on UA dilators. Second, flow response in types 1 and 2 was, on average, 52% of the response in type 3 (data from FIG. 6 ). It is difficult to explain this magnitude by arousals that could not be seen, could not be detected by Fourier analysis, and that were not strong enough to mount a pressor response. Basner and coworkers (46) found that acoustic stimuli applied during spontaneous obstructive apneas decreased their duration by 2 seconds when no overt (greater than 3 seconds) cortical arousal resulted. This was only 20% of the reduction produced by stimuli with overt arousal. This value of 2 seconds overestimates the potency of subcortical arousals; in most cases classified as “no arousal,” there were cortical changes that did not meet standard criteria (see discussion in Basner and coworkers [46]). Thus, the potency, if any, of subcortical mechanisms in opening UA is miniscule.

4. Cortical arousals may be present in unmonitored areas. See online supplement.

5. In a minority of type 1 and 2 observations, there were changes in one or more high-frequency bands, but they were not sufficient to increase total high-frequency power above baseline (see Table E1 in online supplement). These are almost certainly analytical or technical artifacts (see online supplement). Furthermore, neither flow response (see FIG. E7A in the online supplement) nor heart rate response (see FIG. E9 in the online supplement) was different in these cases from responses where there were no EEG changes at all.” (Younes 2004)

“Evidence for Nonessentiality of Arousal. This study produced much evidence that arousal is not essential for UA opening:

1. The relation between Tflow and Tarousal was quite inconsistent (FIG. 3 ). If arousal causes opening, why does it occur sometimes before and sometimes after opening, even in the same patient? Most patients (78%) displayed different types at different times and, even within the same response type in the same patient, the difference between Tflow and Tarousal varied considerably (see FIG. E6 in the online supplement). This strongly suggests that the association is incidental.

2. Type 3 was much less frequent when obstruction was milder (FIG. 4A). If arousal is required for UA opening with a severe hypopnea, why is it not required with a milder one? That UA opening can occur without arousal at any obstruction severity indicates that the relation between UA dilators' activation and opposing forces is such that the dilators prevail, in due course, without arousal. If so, it is difficult to envision a scenario whereby UA dilators can prevail without arousal at one level of severity but not at a higher one (FIG. 9 ).

3. Frequency of UA opening without arousal increased with delta power (FIG. 4B). Why should arousal be needed in light but not deep sleep? Obstruction was no less severe. Latency to UA opening was also not affected by delta power. Thus, dynamics of compensatory responses were not different. Arousal threshold increases with delta power (10-12). The most reasonable interpretation is that arousal-independent compensatory mechanisms are capable of opening the UA, but when arousal threshold is low, arousal occurs first or concurrently.

4. Dingli and coworkers (7) and Rees and coworkers (2) reported that duration of spontaneously occurring apneas— hypopneas was not different whether or not an arousal occurred (i.e., type 1 vs. types 2 and 3). Perhaps, it may be argued, that in a minority of events (i.e., type 1) arousal-free compensation is possible but in the majority (types 2 and 3) arousal is needed. However, in this study latency to opening was the same whether arousal occurred before (type 3) or after (type 2) opening (FIG. 5 ). What was different was latency to arousal (FIG. 5 ). The inescapable conclusion is that arousal is irrelevant to when UA opening occurs.

It follows that if a patient opens UA without arousal even once, he/she will have demonstrated an ability to open without arousal under other conditions if arousal does not occur first. That 78% of patients developed type 1 or type 2 response in at least one dial-down (see FIG. E6 in the online supplement) implies that the great majority do not need arousal to open the UA.

Only 18 patients (22%) had exclusively type 3 responses. Ten of these, however, developed lengthy periods of stable breathing (greater than 50% of sleep time) during polysomnography in body positions where dial-downs showed complete obstructions (n=8) or moderate hypopneas (n=2). This is unequivocal evidence that a patient can mount effective compensation without arousal. Thus, only eight patients (10%) failed to open the UA without arousal at any time. It is possible that a small minority needs arousal. It is, however, also possible that in such patients arousal threshold was consistently low or that the mechanical abnormalities were sufficiently severe that it was difficult to mount the necessary dilator recruitment without reaching arousal threshold first.

In summary, the present findings indicate that in the vast majority, if not in all, of the patients, arousal is not required for UA opening.” (Younes 2004)

“The conceptual basis of the ASDA criteria is that arousal [as defined by ASDA criteria] is a marker of sleep disruption, a detrimental and harmful thing.” (Halasz et al, 2004) Although cortical activation is the gold standard for definition of ‘arousal,’ several studies show there are different levels of central nervous system activation. At the lower range of ‘subcortical arousal’ responses are those inducing reflex motor responses, autonomic activation, and appearance of slow wave EEG activity such as delta bursts (D-bursts) and K-complex bursts (Kbursts), none of which meet the ASDA definition for cortical arousals and therefore fall into the category of ‘subcortical arousals.’ At the upper range are arousal responses implying a cortical activation represented by microarousals (MA) and phases of transitory activation (PAT), which may include high frequency content but nonetheless do not meet the ASDA definition for cortical (EEG) arousals and therefore fall into the category of ‘subcortical arousals.’

External stimuli may induce significant autonomic and somatic responses without causing an ASDA ‘cortical arousal’: “Somatosensory and auditory stimulation during sleep may result in cardiac, respiratory and somatic modifications without overt EEG activation (Carley et al. 1997; Winkelman 1999).” (Halasz et al, 2004)

“The EEG . . . must be recorded unambiguously to differentiate between sleep and wakefulness. Briefly, in humans a sleep stage I is characterized by a modified alpha rhythm and low amplitude EEG; stage 2 shows the typical spindles (14 Hz) and stages 3 and 4 show an increasing amount of slow waves (1-4 Hz).” (Velluti, 1997)

“Interactions between sleep and sensory physiology have been described, an important one being that any sensory stimulation, if strong enough, will always awaken the sleeping subject regardless of the sleep stage. All sensory systems reviewed demonstrated some influence on sleep and, at the same time, the sensory systems undergo changes that depend on the sleeping or awake state of the brain. Interestingly enough, every sensory system shows an efferent pathway, i.e. centrifugal fibres that reach practically all nuclei of the afferent pathway as well as the receptors themselves. Thus, sensory information entering through the receptors may alter sleep and waking physiology and, conversely, the sleeping brain imposes rules on incoming information.” (Velluti, 1997)

“As the only sensory system remaining [fully] active while asleep (at least in a microosmatic animal) a special relationship may be considered to exist between the auditory system and sleep. It seems to act as a constant guardian to signal danger, a predator or perhaps also prey. A second characteristic that makes the auditory system unique is its conspicuous efferent component, featuring a complex anatomy located in parallel to the classic ascending pathway (Rassmusen 1946; Desmedt 1975; Saldana et al. 1996), and functioning as an input controller particularly through the action of its most peripheral stages, the olivo-cochlear system (Galambos 1956; Fex 1962; Guinan 1986; Velluti and Pedemonte 1986; Velluti et al. 1989).” (Velluti, 1997)

“Upon sensory stimulation, a special evoked EEG pattern is described (Loomis et al. 1938) designated as the K-complex. Appearing in response to sensory stimulation, as well as spontaneously, K-complexes are observed in response to visual, somesthetic and to auditory stimulation although the latter is most effective (Halasz and Ujszaszi 1988). The K-complex response to auditory (click) stimulation is large and less variable during light sleep (stage 2); while during stage 4 SWS there is no sensory-evoked modifications of the electrical activity (Davis et al. 1939).” (Velluti, 1997)

“Experimental data gathered using the far field-potential recording technique in humans showed no sleep effects on the brainstem auditory evoked potentials (Amadeo and Shagass 1973; Picton et al. 1974; Osterhammel et al. 1985; Bastuji et al. 1988). In addition, the constancy of the response was maintained whether sound stimuli were either of high or low intensity (Campbell and Bartoli 1986). Moreover, normal brainstem auditory evoked potentials were observed during sleep/waking in apnoeic patients (Mosko et al. 1981).” (Velluti, 1997)

“The trigeminal sensory nuclear complex conveys sensory information from the face and mouth to higher brain regions such as the thalamus and cortex. In 1965, Hernandez-Peon et al. reported that tactile evoked-field potentials recorded at the trigeminal nucleus level showed a powerful suppression during W [wakefulness] and PS [paradoxical (REM) sleep], while a facilitatory effect was present during SWS [slow wave sleep]. This phenomenon, the increased amplitude of the evoked response during SWS, has been seen in most reports of sensory system evoked-field potentials, e.g. visual (Garcia-Austt 1963; Palestini et al. 1965), auditory (Herz 1965; Hall and Borbely 1970), and in the auditory nerve compound action potential (Velluti et al. 1989) as well as in the electroretinogram (Galambos et al. 1994).” (Velluti, 1997)

“Somatosensory signals are conveyed along two ascending systems in the spinal cord, i.e. the dorsal-column-medial lemniscal system that relays information about tactile sensation and propriocepcion, and the antero-lateral system, carrying chiefly pain and temperature sensations. Studying the modulation of synaptic transmission at the level of the dorsal column nuclei in the lemniscal system during sleep, Pompeiano's group demonstrated that during PS there is a phasic depression of the orthodromic lemniscal response occurring synchronously with REM bursts (Carli et al. 1967) . . . The incoming somatosensory information from the body is transmitted rostrally by neurons located in the spinal cord dorsal horn laminae, whose axonal projections comprise a number of ascending pathways, including the spinoreticular, the spinothalamic and the spinomesencephalic tracts conveying pain, temperature and to a much lesser extent, tactile sensations. Soja et al. (1993) demonstrated that this sensory input changes its characteristics depending on the sleep/wake cycle.” (Velluti, 1997)

“The electrical activity of the olfactory bulb is modulated by the sleep/waking cycle. The waves, bursts of 40-50 c/s simultaneous with respiration, increase during attention or sniffing and decrease during SWS to disappear during PS; this phenomenon has been explained by an inhibitory centrifugal control (Hernandez-Peon et al. 1960) . . . .

In humans, only limited data on the topic are available. The existing data indicate (Badia et al. 1990) that a behavioural awakening reaction occurs when olfactory stimuli are presented during sleep.” (Velluti, 1997)

“These findings might corroborate the hypothesis of the existence of 2 separate neural systems integrated in the arousal network and undergoing different modulatory influences.”

Further studies indicate that overall, increasing ventilatory effort may be the most important stimulus to arousal from sleep, and the stimulus to arousal from hypoxia and hypercapnia may be mediated principally through stimulating an increased ventilatory efforts.

These considerations raise the question of possible manipulation of the arousal response to maximize the beneficial effects related to facilitating resumption of airflow, but minimize the adverse consequences related to sleep fragmentation and post-apnea hyperventilation. These latter effects appear to relate more to cortical than brainstem arousal.

Furthermore some studies concluded that: “The current findings suggest that strategies of induced arousal, at an intensity level stimulating respiration while avoiding recruitment of the ascending arousal system and its potential effects of sleep disruption, could have potential application as a therapeutic modality. Apnea was detected by tracheal breath sounds which were picked up by microphone . . . stimulation decreased the frequency of apnea episodes and the longest apnea duration. This resulted in an increase in arterial oxygen saturation. Moreover stimulation decreased sleep stages I and II, and increased stages III and IV. These findings suggest that stimulation using the apnea demand-type stimulator may be an effective treatment for OSA”.

Other research has determined that: the Psa (Blood Pressure) and HR (Heart Rate) increased more and the SV (Stroke Volume) decreased more in the apnea that was terminated by an EEG (cortical) arousal compared with the apnea without an EEG (subcortical) arousal.

Furthermore externally applied stimulus is reported to cause a “trend among our subjects to shortening of the apnea immediately after the stimulated apnea; that is, the effect of the tone appeared to extend to the next apnea. We would hypothesize that the acoustic stimuli did alter sleep state and thus arousal threshold such that the immediately succeeding apnea might have been more susceptible to concurrent respiratory afferent stimuli.” This took place in spite of the trend for Obstructive Sleep Apneas to increase in both frequency and duration during a nights sleep.

“Using sound stimulation with 90-dB tones at 625 Hz, 1/1 to ⅕ min rate delivered by headphones, Levine et al. (1987) found that the number of natural arousals decreased during nights with frequent (1/1 min) stimulation resulting into abundant evoked arousals.” (Halasz 2004)

“One animal study reported that the [stage two slow wave sleep] SWS-2 (in rats), with high delta wave power, showed the highest arousal threshold when a non-meaningful sound was used (Neckelmann and Ursin 1993).

Conflicting results have been reported concerning sound stimulation effects on sleep in animals. Continuous high intensity white-noise stimulation resulted in almost complete deprivation of [paradoxical sleep] (PS) in rabbits (Khazan and Sawyer 1963) while in rats, the same stimulation led to PS reduction without a decrease in the amount of [slow wave sleep] (SWS) (Van Twyver et al. 1966).” (Velluti 1997)

“Very interesting results were reported by Buendia et al. (1963) who observed that the responsiveness of a conditioned cat to a 5 kHz ‘positive’ tone (reinforced with classical and instrumental conditioning) during wakefulness was characteristic but different in each sleep phase, measured by the tone's capacity to awaken the animal” (Velluti 1997)

“During sleep, one normal reaction to any supra-threshold sensory stimulation is a return to a wakeful condition. Moreover, upon sensory stimulation, a special evoked EEG pattern is described (Loomis et al. 1938) designated as the K-complex. Appearing in response to sensory stimulation, as well as spontaneously, K-complexes are observed in response to visual, somesthetic and to auditory stimulation although the latter is most effective (Halasz and Ujszaszi 1988). The K-complex response to auditory (click) stimulation is large and less variable during light sleep (stage 2); while during stage 4 SWS there is no sensory-evoked modifications of the electrical activity (Davis et al. 1939). Human auditory responses recorded from the vertex have been reported by several investigators using similar approaches and obtaining similar results. In all subjects the major changes in the auditory evoked response, in changing from the awake state to the four stages of SWS sleep was a consistent increase in peak to peak amplitude. During PS the amplitude was lower and approximated that of the awake state. The later waves of the response were of longer latency during both sleep phases, SWS and REM (Vanzulli et al. 1961; Davies and Yoshie 1963; Williams et al. 1963; Weitzman and Kremen 1965; Ornitz et al. 1967). Campbell et al. (1992) in a comprehensive review of evoked potentials and information processing during sleep, arrived at some interesting although debatable conclusions. The experimental data gathered using the far field-potential recording technique in humans showed no sleep effects on the brainstem auditory evoked potentials (Amadeo and Shagass 1973; Picton et al. 1974; Osterhammel et al. 1985; Bastuji et al. 1988). In addition, the constancy of the response was maintained whether sound stimuli were either of high or low intensity (Campbell and Bartoli 1986). Moreover, normal brainstem auditory evoked potentials were observed during sleep/waking in apnoeic patients (Mosko et al. 1981) . . . . Thus, it is hypothesized that during different CNS states (e.g. sleep) control must be exerted as far as the most peripheral auditory regions. We are beginning to observe this, both from newly gathered experimental data as well as from teleologically evaluating the complex auditory efferent system. The data on the sleep effects on middle latency auditory evoked potentials (potentials perhaps arising from the reticular formation, thalamus, and primary cortex) are much less consistent. While early studies indicated that these components were either not affected or only slightly affected by sleep, more recent reports showed marked changes, most notably in the later evoked potential components (Osterhammel et al. 1985; Erwin and Buchwald 1986; Ujszaszi and Halasz 1986), although see Campbell, Bell and Bastien. (1992). The later components of the evoked potential, also called the slow potentials or late auditory evoked responses, are the most altered during sleep. A clear N1-P2-N2 complex exists during W with no discernible P1. During SWS and stage 2, N1 is attenuated while P2 may increase in amplitude. On the other hand, during PS, N2 becomes larger while the general morphology of the late components approaches that of W. The P3 wave, considered an endogenous potential, is not visible when subjects are awake and distracted, hence ignoring the auditory stimuli. Similarly, P3 can not be detected during sleep (Campbell et al. 1992) although Bastuji et al. (1990) suggested that P3 may be present during PS.

The amplitude of the averaged auditory nerve compound action potential and the microphonic potentials, in response to clicks and tone-bursts, have been reported to change throughout the sleep/waking cycle.” (Velluti 1997)

“80% of the recorded cells changed their firing during binarual stimulation while 85% did so during ipsilateral sound stimulation. In addition, shifts in the discharge pattern were observed in 15% of the cells recorded on passing from W to sleep while the most striking change, observed in decreasing firing units, was the near-absence of responses in PS during the last 40 ms as judged from the post-stimulus time histogram (stimuli: 50-ms tone bursts).” (Velluti 1997)

“The organization of human sleep is extremely sensitive to acoustic stimuli and noise generally exerts an arousing influence on it.” (Velluti 1997)

“Auditory sensory gating is a rudimentary physiological assay of the brain's ability to filter out or ‘gate’ extraneous acoustic information. This phenomenon is generally measured by observing the reduction in magnitude of particular auditory evoked potentials as a function of stimulus repetition (i.e. stimulus redundancy). Evoked potential attenuation of this type has been alternatively interpreted as a reflection of the brain's finite ‘recovery function’ (e.g. Davis et al., 1966).” (Kisley 2001)

“Rapid eye movement (REM) sleep is a particularly appropriate candidate ‘state’ for the measurement of component P50 sensory gating. During REM sleep, the activity of noradrenergic neurons in the locus coeruleus are greatly reduced (Hobson et al., 1975), potentially removing the confounding effect of norepinephrine. Furthermore, the possible influence of selective attention on sensory gating becomes irrelevant if subjects are asleep. Waveform measurements necessary to assess gating can be achieved because all components of the auditory evoked potential, including P50, are present during REM sleep (Williams et al., 1962; Weitzman and Kremen, 1965). Further, differential processing of sequential acoustic stimuli occurs during REM sleep as reflected in later evoked potential components, such as the mismatch negativity (Loewy et al., 1996, 2000; Nashida et al., 2000) and P300 (Sallinen et al., 1996; Cote and Campbell, 1999a,b). Nevertheless, only one previous study has examined auditory evoked potential attenuation as a function of stimulus repetition during REM sleep: Ornitz et al. (1972, 1974) found that component N2— a negative wave occurring about 250 ms after stimulus onset—exhibits better recovery (i.e. poorer gating) during REM sleep than during waking in healthy children.” (Kisley 2001)

“Electroencephalographic signals were recorded (Neuroscan Acquisition System; Sterling, VA) from each subject during two separate sessions: one during waking, and one during sleep. Half of the subjects underwent the waking recording first. For both sessions, the continuous electroencephalogram (EEG) was recorded from a vertex electrode (Cz) referenced to the right ear, and the electrooculogram (EOG) from a bipolar configuration between electrodes directly above and lateral to the left eye. During sleep recordings, the electromyogram (EMG) was also recorded with a bipolar submental configuration. A ground electrode was attached to the left ear. All electrode impedances were maintained below 10 kV. Average auditory evoked potentials were computed from the EEG activity immediately following acoustic clicks (0.04 ms pulse, filtered between 20 and 12 000 Hz), which were delivered through insert earphones. The click intensity was adjusted to 40 dB above each subject's hearing threshold (determined by method of limits; thresholds for all subjects were within a 10 dB range), separately for each ear. Clicks occurred in pairs (0.5 s inter-click interval), and pairs occurred every 10 s. For the awake recording, supine subjects were instructed to keep their eyes open and still during auditory stimuli (which occurred every 10 s), and to apprise the experimenter of any difficulty in staying awake or keeping their eyes open. After a 5 min acclimatization, recording began and lasted until 30 min of data had been acquired. Each subject decided during the experiment whether acquisition continued unabated for 30 min (N=4), or whether this time was broken up into two 15 min blocks (N=4), or 3 blocks of 10 min each (N=2) . . . .

For acquisition, EEG signals were amplified 5000 times and filtered between 0.1 and 200 Hz, EOG amplified 1000 times and filtered between 0.1 and 100 Hz, EMG amplified 12 500 times and filtered between 5.0 and 200 Hz. Occasionally, a 60 Hz bandstop filter was used to attenuate power line artifact. All channels were sampled at 1000 Hz. Continuously recorded data were converted from Neuroscan's Scan 4.1 software format to ASCII format, then imported into the Matlab software package (Mathworks; Natick, MA) for further analysis with custom programs. Single trial evoked potentials were isolated from the continuous EEG by aligning the signal with stimulus markers to the nearest millisecond. These trials were filtered with a bandpass (5-100 Hz) that includes those frequencies which contribute the most power to auditory middle latency components (Suzuki et al., 1983), and a bandstop filtered at 60 Hz. All filters were applied both forward and reverse to eliminate phase distortion (Matlab's ‘filtfilt’ function).

Continuous recordings were divided into 20 s epochs for scoring of sleep stages, and initially screened for REM sleep periods by simple power analysis: the average power in the EEG channel between 12 and 14 Hz (‘spindle’ band), the total power in the EOG channel, and the total power in the EMG channel were plotted as a function of time for the entire recording session (e.g. FIG. 1 ). Putative REM sleep episodes were then easily detected as periods of greatly reduced spindle power, increased EOG power (due to REMs), and reduced submental EMG power (due to reduced muscle tone). Final determination of sleep stage was achieved by visual inspection of the EEG, EOG, and EMG signals in 20 s epochs, and the application of traditional criteria as described in Rechtschaffen and Kales (1968). Average auditory evoked potentials were computed from EEG signals recorded during the initial 30 min of the first REM episode of the night that lasted 30 min or longer. A ‘REM episode’ was considered to begin when two consecutive 20 s epochs were scored as REM sleep, and end when 3 or more consecutive epochs were scored as non-REM sleep or waking. A REM episode defined in this manner could include epochs with movement artifact and arousals as long as the subject returned to REM sleep within two epochs . . . .

Pairs of clicks (0.5 s inter-click interval) were presented every 10 s throughout the recording session, and average evoked potentials computed separately for each click of the pair. For each of the individual evoked potential components, the magnitude of evoked response to the second (‘test’) click of a pair was then compared with the magnitude of evoked response to the first (‘conditioning’) click. Specifically, a ratio of the magnitudes, the test/conditioning or ‘TIC’ ratio, was computed to quantify sensory gating. A T/C ratio close to 0 indicates robust suppression (very small test response compared with conditioning response) and a T/C ratio of 1 indicates essentially no sensory gating (test and conditioning responses were comparable in magnitude). In the general population, T/C ratios for component P50 range between 0 and well over 1, but are generally below 0.4 for subjects without a personal or family history of psychosis (Siegel et al., 1984; Waldo et al., 1994) . . . .

Auditory evoked potential components were defined as follows: P30, positive wave, peaking between 25 and 45 ms; P50, positive, peak 45-65 ms; and N100, negative, first trough greater than 75 ms . . . . To maintain consistency with previous sensory gating literature, magnitudes of these components were measured from preceding trough to peak (P30 and P50: Nagamoto et al., 1989) and from preceding peak to trough (N100).” (Kisley 2001)

“In contrast to Erwin and Buchwald (1986b) who reported a virtual absence of component P50 during stage II sleep for all 14 of their subjects, we found clear evoked potential components corresponding to P50 in 8 of our 10 subjects during non-REM (mostly stage II) sleep. Further, we found the mean amplitude of P50 during non-REM sleep to be approximately equal to that for REM sleep. Methodological elements which differed between our studies might be responsible for the discrepancy. Erwin and Buchwald (1986b) filtered auditory evoked potentials between 10 and 300 Hz, whereas we filtered between 5 and 100 Hz. Since evoked potentials were recorded with a wide bandpass (0.1-200 Hz) for the present study, and subsequently filtered digitally, we are able to compare the effect of different cut-off frequencies on the magnitude of wave P50. The example shown in FIG. 4A demonstrates that a filter very similar to that used by Erwin and Buchwald (10-200 Hz) does not reduce the amplitude of P50 evoked during non-REM sleep. Thus, the difference in filter parameters probably cannot explain the discrepancy in results between the present study and that of Erwin and Buchwald (1986b). We feel the difference between acoustic stimulation paradigms utilized in the two studies is more likely to be responsible for the disparate findings regarding the magnitude of wave P50 during non-REM sleep. The critical variable is probably the inter-click interval. Erwin and Buchwald (1986b) presented auditory clicks in trains at 1 Hz, whereas we employed the paired-click paradigm. Average evoked potentials were computed from all evoked responses in a click-train for the former (inter-click interval, 1 s), and only from the conditioning evoked responses for the latter (interclick interval, 10 s). Like Erwin and Buchwald, Jones and Baxter (1988) reported the disappearance of component P50 during non-REM sleep when clicks were presented in rapid trains (5 Hz), even though very wide-band filters (0.3-3000 Hz) were applied to the evoked potential signal. In comparison, studies using click-trains at slower rates of presentation (0.5 Hz or less) have consistently reported the robust presence of component P50 across all sleep stages, including II, III, and IV in adults (Williams et al., 1962; Weitzman and Kremen, 1965; Kevanishvili and von Specht, 1979) and children (Barnet et al., 1975). To summarize, vertex component P50 appears to be measurable under non-REM sleep for most subjects in response to the conditioning click for the paired-click paradigm, and also in response to clicks during the click-train paradigm for rates of 0.5 Hz or less, but not for rates of 1 Hz or more.” (Kisley 2001)

The kind of stimuli provokes different responses in human subjects: “Previous studies using single-modality paradigm have shown that sensory gating systems, which select relevant sensory information, remain functional during sleep.” Halasz et al., 2004; Kisley et al., 2001; Velluti, 1997; which are hereby incorporated by reference.

“In humans, relevant stimuli (e.g. sound>65 dB, one's own name, experimental noxious stimulation) induce arousal response more frequently and results in more intense response compared with irrelevant stimuli . . . . Simultaneous multi-modality sensory inputs from body surface and from other organs (e.g. ear) not only increase the amount of sensory inputs but also can maximize the relevance of stimuli.”

Central Sleep Apnea results from the brain failing to signal the muscles to breathe. The neural drive to the respiratory muscles discontinues for a brief period of time. These transients may continue throughout the night for periods from ten seconds to as long as 2 to 3 minutes. The physiological effects are similar to those of Obstructive Sleep Apnea.

Mixed Sleep Apnea is a combination of Obstructive Sleep Apnea and Central Sleep Apnea.

There are several known treatments for Sleep Apnea. They consist of physical, electrical, and mechanical methods, surgery, and attempts at pharmacological treatment. The treatment regimen is tailored to the individual, and is based on the medical profile of the patient being treated.

The most common effective treatment for patients with sleep apnea is nasal continuous positive airway pressure (CPAP). In this form of treatment, the patient wears a mask over the nose while sleeping. The mask is connected to a compressor that creates a positive pressure in the nasal passages. The continuous positive airway pressure system prevents the airway from closing or becoming obstructed during sleep. The air pressure from the continuous positive airway system is constant, and can be adjusted to best suit the individual's apnea condition. The air pressure in the continuous positive airway pressure system must be adjusted so that it maintains an open airway in the patient during all periods of sleep, but does not provide excessive pressure such that the device is bothersome to the patient. U.S. Pat. No. 4,655,213 discloses sleep apnea treatments based on the principles of continuous positive airway pressure. There have also been recent attempts at varying the applied pressure to increase the effectiveness of continuous positive airway pressure treatment. U.S. Pat. Nos. 4,773,411 and 6,539,940 disclose such techniques. The disclosures of these United States patents are incorporated herein by reference.

Another treatment for sleep apnea in certain patients involves the use of a Dental Appliance to reposition oral structures such as the tongue and the lower jaw. This form of treatment is typically performed by a dentist or dental specialist such as an orthodontist.

Surgery has also been performed to treat sleep apnea. In some surgical treatments, the size of the airway is increased. These surgical procedures contain elevated levels of risk in comparison to other treatment methods, and often times are not entirely effective. The form of surgery to be undertaken is specific to the patient and the patient's medical profile. The removal of obstructive tissue in the airway such as adenoids, tonsils or nasal polyps is a common form of surgical treatment for sleep apnea. The surgical correction of structural deformities is also a common form of surgical treatment for sleep apnea.

Another form of surgical treatment for sleep apnea is uvalopalatopharyngoplasty. This procedure removes excess tissue from the back of the throat, such as tonsils, uvula, and part of the soft palate. Somnoplasty is also being investigated as a possible treatment for sleep apnea. Somnoplasty uses radio waves to reduce the size of some airway structures such as the uvula and the back of the tongue.

Other forms of surgical intervention for sleep apnea include maxillo-facial reconstruction. Another form of surgical treatment for patients with severe and life threatening sleep apnea is Tracheostomy. This procedure involves making a small hole in the windpipe that accommodates a tube. The tube is opened only during sleep, and allows a patient to take air directly into the lungs, effectively bypassing any upper airway obstructions. Tracheostomy is an extreme procedure that is very rarely used except for cases of imminent life threatening sleep apnea.

Attempts at pharmacological treatment for sleep apnea have included respiratory stimulants such as theophylline, acetazolamide and medroxy-progesterone, and adenosine. Drugs that stimulate brain or central nervous system activity, such as naloxone and doxapram, have also been used in an attempt to treat sleep apnea. Other drugs that act on the neurotransmitters involved with respiration have also been used in an attempt to treat sleep apnea. These drugs include serotonin, dopamine, tryptophan, fluoxetine, and others.

More recently, systems have been developed for the purpose of clearing upper airway passages during sleep using the electrical stimulation of nerves or muscles. In some cases, these systems require surgical implantation of sensors and associated electronics that detect when breathing has ceased and then stimulate the breathing process. Some hybrid systems have been developed that require surgical insertion of one or more sensors plus external equipment for monitoring the breathing process or moving the obstruction when breathing ceases.

An apparatus has been patented a means for detecting the onset of a sleep related disorder using pulse rate and blood oxygen content information as measured by the device; U.S. Pat. No. 7,387,608 discloses sleep apnea treatments based on those principles. The disclosures of these United States patents are incorporated herein by reference.

An apparatus has been patented a means for detecting the onset of a sleep related disorder using a multiplicity of microphones. The apparatus has the microphones emplaced within a collar worn around the neck of the patient. The apparatus detects breathing sounds, and in an embodiment when it detects breathing that is “substantially different from the recorded at least one signal pattern that is associated with a normal breathing pattern of the person; and creating a stimulus to the person's neck muscles to cause the person to move the person's neck muscles to move the person's head backwards to restore normal breathing before cessation of breathing occurs”, as disclosed in U.S. Pat. No. 6,935,335. The disclosures of these United States patents are incorporated herein by reference.

Summary of the Invention

The present invention is directed to a apparatus and method for detecting and treating Sleep Apnea and Hypopnea by terminating a Sleep Apnea event or Hypopnea episode within seconds of detection.

The invention develops through a Method a Referential set of Parameters specific to the respiration patterns of the specific patient (rather than defining and applying Generic Trigger point Parameter as is the case with other inventions). The multiplicity of Signal Parameters combined with a Fuzzy Control System is more adaptable to the changes of Respiration that occurs during the course of the night. Changes of Respiration which might be interpreted by other inventions such as those who use averaging or weighted moving averaging of invention and determined to be a reversion to a Respiration pattern that is normal for this specific patient. Normal for the patient is established by the Processing of the Referential set of Parameters within the Fuzzy Control System.

The inventions method of using both the root-mean-square deviation of a parameter and the parameters' mean, as opposed to simply averaging or weighted moving averaging of the parameter, to establish a reference point for determination of a parameters' out of bound condition, is a superior method for detecting Apnea events or Hypoxia episodes.

In accordance with the present invention, there is provided a wearable, belt like, apparatus for the treatment of Sleep Apnea events and Hypopnea episodes containing a Microphone and a Plethysmograph. The Microphone and Plethysmograph generate signals that are representative of physiological aspects of respiration. The signals are transferred to an embedded computer. The embedded computer extracts the sound of breathing and the sound of the heart beat by the means of Digital Signal Processing techniques. The embedded computer has means for determining when respiration parameters falls out of defined boundaries for the respiration parameters. This method is for the real-time detection of the onset of a Sleep Apnea event or Hypopnea episode. The embedded computer supplies stimulation signals upon the determination of a Sleep Apnea event or Hypopnea episode to initiate an inhalation. The stimulation is provided in a manner so as to avoid the initiation of a cortical (EEG) arousal and vagal withdrawal of the parasympathetic tone to the heart. The stimulus is applied to the patient by a cutaneous rumble effects actuator and audio effects broadcasting. The actuator is embedded within the invention.

It is a primary object of the present invention to provide a system and method for detecting and terminating an Sleep Apnea event and Hypopnea episode, within seconds of the detection, in a manner that will decrease or eliminate hypoxia, hypercapnia and the disturbance of pulmonary hemodynamics respirations as an Apnea Event or Hypopnea episode could be processed by the present invention.

Technical Problem

Positive Airway Pressure (PAP) systems remain the most effective treatment for sleep apnea. Many patients, however, cannot tolerate the Positive Airway Pressure systems and associated apparatus. Common complaints include discomfort with the applied pressure, discomfort with the mask and equipment, nasal irritation, nasal stuffiness and congestion, airway dryness, mask air leaks and noise, entanglement, claustrophobia, noise of the PAP machine, headaches, abdominal bloating, sore and irritated eyes, and an overall discomfort with the machinery. The noise and general obtrusiveness of the PAP apparatus are often disruptive to another person sleeping with the user.

A significant minority of the people for whom PAP is prescribed (estimated to be 30% to 50%) refuse to use it. A study determined that of the patients who use PAP treatment, it is estimated that 34% use it intermittently (4 nights per week) and/or remove it for part of the night (for this group median nightly usage is 3.1 hours).

Beyond the initial cost of the PAP (>U$500.00) there is a continuing cost of replacement masks. It is recommended that masks be replaced every six months (=>U$100.00/mask).

A study determined that Dental Appliances was successful in treating OSA in an average of 52% of treated patients, with success defined as no more than 10 apneas or hypopneas per hour of sleep. Treatment adherence is variable with patients reporting using the appliance a media of 77% of nights at 1 year.

A Dental Appliance typically has a cost in excess of U$1000.00.

Surgery has inherent risks: its' cost is high, its' success rates vary and over a period of time its' effectiveness fades.

Pharmacological treatments for sleep apnea have not achieved any consistent levels of effectiveness, and often contain side effects.

Systems that clear the upper airway passages during sleep using the electrical stimulation of nerves or muscles. These systems may produce positive results but they also have associated risks due to surgery, may need replacement at later times (requiring additional surgery), and may have higher costs and lower reliability than the more traditional treatments. In addition, the hybrid systems also have the accompanying physical restrictions and accompanying disadvantages associated with connections to the external equipment.

An apparatus whose means for detecting the onset of a sleep related disorder relies on blood oxygen content information cannot determine the onset of a sleep order in real time. Oxygen saturation level diminishment always lags the cessation of breathing because it takes time for the as oxygen in the bloodstream to used up by bodily processes. Hypoxia and hypercapnia will occur.

An apparatus whose sole means for detecting the onset of a sleep related disorder relies on detecting the sounds of breathing can be confused by extraneous noises, coughing, wheezing and other internally generated biologic noises. In addition in order for both the microphones and stimulus devices to work most effectively they must be in close contact with the neck and this constriction may prove to be unacceptably uncomfortable to the patient.

Many of these devices provide a single type of auditory stimulus (a fixed tone of varying intensity) and/or mechanical stimulus (a vibrator).

For example, U.S. Pat. Nos. 7,387,608 discloses such techniques. It is Claimed that: “The method of arousing the patient from sleep at the onset of a sleep apnea event will decrease or eliminate the occurrence of sleep apnea, arrhythmia, and partial epilepsy over time,”

These methods of stimulus may prove to be initially effective in reducing the numbers of Apnea events through a process of Conditioning. However, with Conditioning there co-exists Habituation. These are two interacting psychological phenomena with a number of similarities. In Conditioning, an animal is exposed to some events, and as a consequence, it learns to associate a certain behavior with a specific situation. In Habituation too, an event occurs repeatedly, but in this case, the reaction of the animal wanes with repeated exposure.

The dynamics of Habituation is very similar to the extinction of a response that has previously been learned during Conditioning. In both cases, the response becomes less probable or weaker with each occurrence with the event. There is one large difference between the two situations, however. In extinction, a learned response is weakened, but in Habituation the reaction that dies away is typically an innate orienting reaction. Conditioning may indeed lead to extinguishment of Sleep Apneas events or the opposite may occur; Habituation might lead to the patient ignoring the stimulus. If Habituation occurs then Sleep Apnea events would continue until they spontaneously terminate.

Solution to Problem(s)

Therefore, there is a need in the art for an improved system and method for treating Sleep Apnea events and Hypopnea episodes. In particular, there is a need in the art for a system and method that does not create other types of sleep disturbing effects, does not require surgical implementation, does not involve the use of a complicated apparatus, does not include the use of pharmaceuticals, does not require the intervention of health professionals, and does not have the high costs associated with some of the types of treatments currently in use.

Therefore, there is a need for a system and method for treating Sleep Apnea event and Hypopnea episode by terminating a Sleep Apnea event and Hypopnea episode in real time that minimizes the disturbance to pulmonary hemodynamics.

Therefore, there is a need for a system and method for treating Sleep Apnea event and Hypopnea episode that is easy to use by the patient, comfortable, and less expensive than other methods of treatment.

Advantageous Effects of Invention

An Advantageous Effect of Invention is the superior method of detection of Sleep Apnea events and Hypopnea episodes:

Using the standard deviation of a parameter in conjunction with the parameters' mean and a rules based processing (Fuzzy Logic) as opposed to using only a parameters' mean as a reference point for determination of a parameters' out of bound condition (excursion) leads to the diminishment of the occurrence of the invention detecting a false Apnea event or Hypoxia episode.

In the situation where the parameters' mean is the only reference, a single excursion beyond an established limit leads declaration of an Apnea event or Hypoxia episode. Conversely, with this method of the invention, when an excursion is determined, a further determination is performed to establish if the excursion is smaller than every member of the set of parameters that were gathered during the Self-calibrations processes. For while an excursion might be smaller than the mean of the parameter that was calculated by the processes the Self-calibrations, it might be greater than any single parameter that formed the set of parameters that were determined to be “normal” for this specific patient and which formed the reference set of parameters.

The use of rules based processing (Fuzzy logic) allows the invention to evaluate the significance of excursions and make decisions as to whether as excursion merits initiating Stimulus.

The invention analyzes a multiplicity of parameters derived from redundant apparatus to detect respirations. The use of rules based processing (Fuzzy logic) allows the invention to evaluate the significance of excursions of any single parameter or any combination of parameters from the redundant apparatus and make decisions as to whether as excursion merits initiating Stimulus.

Another Advantageous Effect of the Invention is its' ease of use. Many of the patients who would use the invention are both obese and old(er). The invention is simple to don. The invention uses plain language commands to guide the patient in to properly position the invention.

Another Advantageous Effect of the Invention is it is not an encumbrance. The sleeping patient is not physically constrained. This is important in light of the fact that many of the patients have enlarged prostrates which, in many cases, necessitates frequent urination during the night.

Another Advantageous Effect of the Invention is that it is less expensive that most other solutions. From the perspective of overall costs:

It does not require the programming of baseline parameters. Baseline parameters that have to be entered into an apparatus would require that there be an evaluation of the results from the patients' polysomnography and using a method to establish baseline criteria. The invention self determines the baseline parameters, thereby eliminating any requirement for determination of baseline parameters performed outside of the system or entry of baseline parameters into the system.

There are no replacement components. Other devices require periodic replacement of key components, at a considerable expense.

The invention is no more expensive that the average price of the most popular form of treatment for Obstructive Sleep Apnea (CPAP).

Another Advantageous Effect of the Invention is that it can be used in conjunction with the most popular form of treatment for Obstructive Sleep Apnea (CPAP) or as an alternate, independent form of treatment. There is a significant minority or patients who use the CPAP intermittently. Using the invention during those times that the patient is not using CPAP would continue the benefit to the patient that is realized by maintaining normal blood oxygen and carbon dioxide levels.

Another Advantageous Effect of the Invention is it is self-adapting; it self-determines referential baselines for the specific patients' normal respiration patterns. One of the definitions of Obstructive Sleep Apnea is interruptions in airflow of at least 10 seconds. The invention may, depending on the normal respiration pattern of that patient, establish a different baseline as to what an interruption of airflow in seconds would be.

By immediately applying a Stimulus that has been determined to initiate an inhalation at the lowest level of stimulation, the effects on the physiology of the patient of the Apnea event or Hypoxia episode will be minimized.

Another Advantageous Effect of the Invention is that there are devices that ramp up the stimulus (be it the frequency of a mechanical vibrator and/or audio and/or amplitude) until respiration is restored. This takes time, in which case the deleterious effects of declining blood oxygen and increasing blood carbon dioxide accrue, and if it overshoots (there being a delay between the time a stimulus is applied and the reaction of the patient to it) it could lead to a heightened waking than is required to terminate the Apnea event or Hypoxia episode.

Another Advantageous Effect of the Invention is that it is self-adapting; it self-determines referential baselines for the type of Stimulus that is required to terminate an Apnea event or Hypoxia episode. Research has shown that the amount of stimulus required to initiate an inspiration changes in cycles during sleep. The invention continuously evaluates the Stimulus required to terminate an Apnea event or Hypoxia episode.

Another Advantageous Effect of the Invention is that it can supply a very wide range of Stimulus. It has a multiplicity of embedded Audio files and Haptic pattern files, each with a distinct irritation index. The invention will determine which files produce the Stimulus required to initiate an inhalation at the lowest level stimulation. Since there are many file combinations that will produce the Stimulus required to initiate an inhalation at the lowest level stimulation, the invention can avoid Habituation while maintaining the benefit of Conditioning.

BRIEF DESCRIPTION OF DRAWINGS

The invention will be described by reference to the following drawings, in which like numerals refer to like elements, and in which:

FIG. 1 is a top and Bottom External view of the present invention;

FIG. 2 is a Cross-section view;

FIGS. 3A, 3B, and 3C are Block Diagrams of the manner in which Microphone and Plethysmographic sensor data is converted into Signals;

FIG. 4 is a Block diagram of the Electronic and Electrical elements of the invention;

FIGS. 5A, and 5B are Block Diagrams of the Training and Monitoring Processes;

FIG. 6 is a Block Diagram of the Fuzzy Control System;

FIG. 7 is a diagram of a Patient wearing the invention; and

FIG. 8 is a Block Diagram of Portrait Development.

DESCRIPTION OF EMBODIMENTS

Accordingly, embodiments of the present invention are provided that meet at least one or more of the following objects of the present invention.

In one embodiment, a wireless auditory prompter(Bluetooth Earbud) is mounted in the patient's ear and is activated by the stimulation signal to emit an acoustic stimulus which is heard by the patient but is inaudible to others. This embodiment provides a sound to initiate inhalation without requiring other intervention.

In another embodiment, a wired auditory prompter is mounted in the patient's ear and is activated by the stimulation signal to emit an acoustic stimulus which is heard by the patient but is inaudible to others. This embodiment provides a sound to initiate inhalation without requiring other intervention.

In another embodiment, a loud speaker is embedded within the invention and is activated by the stimulation signal to broadcast an acoustic stimulus which is heard by the patient. This embodiment provides a sound to initiate inhalation without requiring other intervention.

In another embodiment, the computer detects the absence of a heartbeat and activates an audible alarm by the loud-speaker embedded within the present invention.

In another embodiment, the computer has means to store the calculated amplitude, periodicity, and duration of respiration for each respiration of the collection of known good respirations from the first self-calibration in embedded memory.

In another embodiment, the computer has means to store the calculated values and parameters in embedded memory.

In another embodiment, the computer has means to store the time(s) in which a Sleep Apnea event and Hypopnea episode occurs in embedded memory. In another embodiment, the computer has means to store the time(s) in which a Sleep Apnea event and Hypopnea episodes are terminated in embedded memory.

In another embodiment, the computer has means to export the calculated values and parameters from embedded memory to other devices.

In another embodiment, the computer has means to export the time(s) in which a Sleep Apnea event and Hypopnea episode occurs and from embedded memory to other devices.

In another embodiment, the computer has means to export the time(s) in which a Sleep Apnea event and Hypopnea episode are terminated from embedded memory to other devices.

In another embodiment, the computer has means to import modifications of the computer programs from other devices.

In another embodiment, the computer has means to import modifications of the computer program that comprises the rules based processing (Fuzzy Logic) from other devices.

In another embodiment, the plethysmographic sensor can be implemented using a string potentiometer.

In another embodiment, the plethysmographic sensor can be implemented using strain gauges.

In another embodiment, the plethysmographic sensor can be implemented using accelerometers.

In another embodiment, the plethysmographic sensor can be implemented using Hall Effect components.

In another embodiment, the plethysmographic sensor can be implemented using LEDS and Photo detectors.

In another embodiment, the plethysmographic sensor can be implemented using ultrasonic sensors.

In another embodiment, there might be a plurality of microphones.

In another embodiment, the mechanical tactile sensory stimulator may be implemented using a Haptic Display.

In another embodiment, the mechanical tactile sensory stimulator may be implemented using a Haptic Display comprising shape memory springs.

In another embodiment, the mechanical tactile sensory stimulator may be implemented using a Haptic Display using multiple actuators.

In another embodiment, the mechanical tactile sensory stimulator may be implemented using a Haptic Display comprising rotating drums.

In another embodiment, the mechanical tactile sensory stimulator may be implemented using a Haptic Display comprising electroactive polymers.

In another embodiment, sensory stimulation may be applied optically by the donning of a device that is worn over the eyes and in which LEDs shine light through the eyelids into the pupils.

The foregoing has outlined rather broadly the features and technical advantages of the present invention so that those skilled in the art may better understand the detailed description of the invention that follows. Additional features and advantages of the invention will be described hereinafter that form the subject of the claims of the invention. Those skilled in the art should appreciate that they may readily use the conception and the specific embodiment disclosed as a basis for modifying or designing other structures for carrying out the same purposes of the present invention. Those skilled in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the invention in its broadest form.

Before undertaking the Detailed Description, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document: the terms “include” and “comprise” and derivatives thereof mean inclusion without limitation; the term “or,” is inclusive, meaning and/or; the phrases “associated with” and “associated therewith,” as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, or the like; and the term “controller” means any device, system or part thereof that controls at least one operation, such a device may be implemented in hardware, firmware, or software, or some combination of at least two of the same. Definitions for certain words and phrases are provided throughout this patent document. Those of ordinary skill in the art should understand that in many, if not most, instances, such definitions apply to prior, as well as future uses of such defined words and phrases.

“Measurement” by the Computer in this application is defined as an Analog-to-Digital Conversion. The derivative of Analog-to-Digital Conversion is a numeric value that is representative of the Signals Amplitude at the time that the Measurement is made. Those skilled in the art will understand the method of using Analog-to-Digital conversion.

“Processing”, “Process”, “Monitoring”, and “Method” are used interchangeably in this document and are collectively defined as the application of software programs that are resident within the Computer as means or manner of procedure to accomplishing something. The means and reasons for the Processing will be addressed in detail within this document.

“Stationary” or “quasi-stationary” signals are those in which the statistical distribution of frequencies does not change significantly over the time scale of interest.

“Nonstationary” signals are those whose statistical frequency distribution changes significantly over the time scale of interest.

“Naturalistic” sounds are sounds that are naturally-occurring or that mimic naturally-occurring sounds. Naturalistic sounds are nonstationary and have logarithmically distributed spectrotemporal modulations, as compared with the linearly distributed spectrotemporal modulations of sounds that are not naturalistic.

Other objects and features of the present invention will become apparent from the following detailed description considered in conjunction with the accompanying drawings. It is to be understood, however, that the drawings are designed solely for purposes of illustration and not as a definition of the limits of the invention, for which reference should be made to the appended claims.

For a general understanding of the present invention, reference is made to the drawings. In the drawings, like reference numerals have been used throughout to designate identical elements.

In accordance with this present invention, there is provided an apparatus and method for the diagnosis and treatment of Sleep Apnea and Hypopnea. In one embodiment of the invention, the respirations of the patient are monitored during sleep by the apparatus, which acts as a monitoring system to detect and treat Sleep Apnea events and Hypopnea episodes in the patient. The monitoring system is comprised of an integrated plethysmographic, an integrated microphone, an integrated computer and software program, and methods for applying stimulus to the patient such as an integrated loud speaker, wired and wireless audio, and an integrated rumble effects actuator. The invention is a wearable, belt-like device, the device is fitted around the Thorax or Abdomen of a patient.

At the onset of a Sleep Apnea event or Hypopnea episode the respiratory induced movement (expansion and contraction) of the Thorax and/or Abdomen are significantly reduced. In addition, the movement of air into the lungs is significantly reduced. These decreases are indicators of an onset of a Sleep Apnea event or Hypopnea episode. During sleep, it is normal for the patients' respiration parameters for amplitude, periodicity, and duration of respiration to vary. Discerning between those normal variations in the parameters (for amplitude, periodicity, and duration of respiration during sleep) and abnormal variations in parameters (for amplitude, periodicity, and duration of respiration levels), is performed using a software program that compares those parameters gathered by monitoring parameters (for amplitude, periodicity, and duration of respiration during sleep) to those parameters (for amplitude, periodicity, and duration of respiration) gathered before the patient fell asleep. This method accurately identifies the onset of a Sleep Apnea event or Hypopnea episode and eliminates false determinations.

The embedded computer's software program uses rules based processing (Fuzzy Logic) to determine when Stimulation is to be applied in order to restore airway patency (by inducing inspiration).

When the patient's respiration parameters are determined by the rules based processing (Fuzzy Logic) as showing the onset of an Sleep Apnea event or Hypopnea episode Stimulation is provided.

The present invention may use historical data, software programs, algorithms or subroutines to assist with the determination of the rules based processing (Fuzzy Logic) that are appropriate to the patient. The embedded computer's software program uses rules based processing (Fuzzy Logic) to determine the least amount of Stimulation required to induce inspiration.

The Stimulation is in the form of audio signals and by a cutaneous rumble effects actuator. Rules based processing (Fuzzy Logic) determine the least amount of Stimulation required to induce inspiration.

FIGS. 1 through 8 , discussed below, and the various embodiments used to describe the principles of the present invention in this patent document are by way of illustration only and should not be construed in any way to limit the scope of the invention. Those skilled in the art will understand that the principles of the present invention may be implemented in any suitably modified system for detecting and terminating an obstructive sleep apnea event.

FIG. 1 illustrates one embodiment of the present invention showing External views, Top and Bottom.

The embodiment of the present invention that is illustrated in FIG. 1 has Microphone 125 capable of detecting sounds within the airway of patient (not shown). One type of microphone that is suitable for use in the present invention is the electret microphone. Microphone 125 is attached to the Housing 145 and Housing 145 is detachably fastened around the Thorax or Abdomen of the patient (not shown) with a Belt 165 and Velcro clasp (not shown in FIG. 1 ). Housing 145 is fastened around the Thorax or Abdomen of the patient (not shown) so that Microphone 125 is positioned adjacent to the lungs and in contact with the patient (not shown on FIG. 1 ).

LEDs 115 & 120 are Status indicators. The emitted color that the LEDs display are indicative of operational conditions of the present invention.

Buttons 105 & 110 control the operations of the present invention.

The Microphone 125 is capable of generating signals representative of the sounds of breathing of person 120. When Microphone 125 detects sounds of breathing, it generates a signal. The signal generated by the Microphone 125 is transferred via an individual microphone signal line to signal processing circuitry 200 (shown in FIG. 3 ) contained within Housing 145.

FIG. 2 is a cross-section (side view) of the present invention,

It illustrates that belt 265 has one end attached to Housing 245. The other end of belt 265 enters Housing 245 and is attached to Shuttle 270 and too Spring 290. Shuttle 270 travels within Guide 275. Shuttle 270 is attached to Wiper 280. Wiper 280 is an attachment of Membrane Potentiometer 285.

The expansion of the Thorax or Abdomen during inspiration causes Belt 265 to pull on Shuttle 270 moving it from its' rest position. Shuttle 270 moves within Guide 275 and deforms Spring 290. The movement of Shuttle 270 also moves Wiper 280. Wiper 280 is pressed down on the top layer of Membrane Potentiometer 285, which in turn touches the bottom layer of Membrane Potentiometer 285. The touching of the upper and lower layer of Membrane Potentiometer 285 creates a voltage divider circuit. The output is voltage. The voltage is a direct inferential reading of the magnitude of the expansion or contraction of the Thorax/Abdomen at any time. The Computer processes the voltage as a Signal. The Signal output of Membrane Potentiometer 285 varies in direct proportion to the position of Shuttle 270 within Guide 275.

When an exhalation occurs the Thorax or Abdomen contracts, releasing tension on Shuttle 270. Spring 290 moves Shuttle 270 back towards its rest position within Guide 275. Those skilled in the art will understand the method of using Membrane Potentiometers to sense position. The cutaneous rumble effects actuator 200 is attached to the Housing 245.

The collection of elements of FIG. 2 makeup the Integrated Plethysmographic Sensor.

FIG. 3 is a Block Diagram of the manner in which Microphone and Plethysmographic sensor data is converted into Signals.

Referring now to FIG. 3A the Block Diagram is illustrative of the Signal that is outputtedfrom the Integrated Plethysmographic Sensor 301. Buffer 302 conditions the voltage Signal from Plethysmographic Sensor 301. The voltage Signal from Buffer 302 is the Thorax/Abdomen Movement Signal 303. The Computer (not shown in FIG. 3 ) Processes the Signal 303.

Referring to FIG. 3B the Block Diagram is illustrative of the Process that the Signals of Breathing Sounds 313 and Heart Beat Sound 312 that are extracted. The Microphone 304 detects a multiplicity of Audio Signals. The multiplicity of Audio Signals are comprised of the Audio components of biologic processes (Heart Beats, audio component of the turbulence that occurs in the human respiratory system during respiration, bowels, snoring, wheezing, yawning, coughing, etc) and external interference artifacts. The multiplicity of signals forms a spectrum of Audio frequencies. The elements of the Block Diagram as represented in FIG. 3B (Buffer 305, Bandpass Filter 306, Envelope Detection 307, Log 308, Sum 309, Integrator 310, and Output Scaling 311) act in concert to filter out the extraneous signals so as to export only the Signals of Respiration 313 and the Signals of the Beating Heart 312.

The process is further detailed in the technical paper: Eder, Derek et al. ‘Detection and Analysis of Respiratory Airflow and Snoring Sounds During Sleep Using Laryngeal Sound Discrimination (LSD)’ in 1992 Vol. 14. Proceedings of the 14^(th) Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Volume 14, Part 6, 29 Oct-1 Nov. 1992 Page(s):2636-2637, which is hereby incorporated by reference. This paper describes “a method that is designed to resolve sounds produced by respiratory activities that are commonly distributed at either extreme of a greater than 90 dB amplitude range. The basis of our method, non-linear dynamic range compression, is well known and is often applied in audio sound processing. Our method was specifically designed to provide measures of: (1) relative volumetric changes in airflow during hypopnea and apnea, (2) parametrization of respiratory phase timing and (3) quantitative measures of snoring intensity . . . .

Respiratory airway sounds are transduced by a miniature microphone that is placed over the lateral aspect of the cricoid cartilage at the level of the larynx. This microphone placement is optimal for the minimization of cardiac sounds from the carotid arteries. The microphone element is a miniature electret condenser type with a specified flat frequency response of 20-20,000 Hz. We have encased the microphone element in a small plastic shell with a 2 mm airgap between the microphone and the skin. This airgap cavity is completely closed, without a pressure equalization port . . . the closed cavity design affords more sensitivity and a greater rejection of environmental sound . . . . The microphone shell has a 20 mm lip to facilitate attachment to the skin with a double-sided medical adhesive tape ring.

The amplitudes of cardiac sounds detected by the laryngeal microphone often equal or exceed those of respiration, and would present a formidable confound to the detection of respiratory sounds if they were not removed. Fortunately, there is little significant spectral overlap between cardiac sounds and respiratory airflow sounds. Cardiac sounds predominate below 100 Hz and are effectively removed with low-order high-pass filtering that comers at 200 Hz. While the spectra of cardiac sounds and snoring may overlap, their great difference in amplitudes allows uncompromised detection of snoring even after highpass filtering. We have implemented a three-pole Cauer filter for cardiac sound rejection. This filter stage also eliminates any SO/60 Hz power mains noise introduced into the system.

Because the LSD method does not incorporate frequency domain analysis, we are able to preserve the desired information content of the respiratory signal in its amplitude envelope. This enables the digitization of the LSD signal at sampling rates below 25 samples/sec. The sound envelope is recovered using full-wave rectification and low-pass filtering. Prior to rectification, the output of the cardiac sound filter is low-pass filtered at approximately 5 KHz to remove any potential high frequency noise such as RFI. Dynamic range compression of approximately 90 dB is effectively obtained by a logarithmic transformation of the respiratory sound envelope. The final stage of the LSD is devoted to output gain scaling and the suppression of DC baseline offsets. These offsets can arise from a variety of sources including continuous environmental sounds, rectified RFI/EMI and temperature drift in the log amplifier. The suppression of DC offsets is performed adaptively by a negative feedback loop. Negative feedback correction is produced by averaging the LSD signal output with a long time-constant integrator, followed by differential summation of the error with the original signal. A resistance multiplying integrator achieves a time constant of approximately fifty-five seconds using capacitors smaller than luF.” (Eder, 1992)

The Computer (not shown in FIG. 3 ) processes the exported Signals. Those skilled in the art will understand this method to extract specific Audio Signals from a multiplicity of Audio Signals.

Referring again to FIG. 3C. The Signals that are derived by the Plethysmographic Sensor 301 and the Microphone 304 are Measured by the Computer (not shown in FIG. 3 ). Each Signal is Measured for three (3) discrete Parameters. The Measurement quantity is assigned a numeric value that represents a direct inferential reading of the specific Signal Parameter. The Parameters that are Measured are the: Amplitude 313 of the Signal. The Amplitude 313 is representative of the expansion of the Thorax or Abdomen during an inspiration. Duration of the Signal 314. The Duration of the Signal 314 is the amount time that it takes for an discrete inspiration and exhalation to be completed.

Periodicity of the Signal 315. The Periodicity of the Signal 315 is the time between discrete exhalations.

FIG. 4 is a Block diagram of the Electronic and Electrical elements of the invention.

The operation of the invention is illustrated in FIG. 4 . It is made up of a number of electronic component sections:

PIC Computer 409 is the Computer of the invention.

On/Off Switch 401 activates and deactivates the invention.

Control1 Switch 402 activation is the method wherein that patient interacts with the invention.

Status LED2 403 is a multicolor LED. The color that it presents to the patient indicates the status of the invention.

Status LED1 404 is a multicolor LED. The color that it presents to the patient indicates the status of the invention. Battery

Pack 405 provides electrical power to the invention.

FLASH RAM 406 contains the Force Portraits 601, the Fuzzy Control System Rules, and the Processing program instructions. The Computer 409 and it exchange data over a signal buss. SRAM 407 contains the results of arithmetic computations by the Computer 409. The Computer 409 and it exchange data over a signal buss. Clock Oscillator 408 is the Inventions clock. BlueTooth 410 is the section that receives Audio Portrait Signals, Alarm Signals, and Training Period 1 & 2 spoken commands, converts the signals into Bluetooth formatted Signals and wirelessly transmits the Audio Portrait Signals to a Bluetooth wireless Earbud 715 (not shown if FIG. 4 ) worn by the patient. Speaker 411 Audio Portrait Signals, Alarm Signals, and Training Period 1 & 2 spoken commands and broadcasts them to the patient.

USB I/O Port 413 is the means by which external devices communicate with the Computer 409. Signals 414, 415, and 416 are the busses by which the Signals are received by the Computer 409 for Processing.

FIG. 5 is a Block Diagram of the Training and Monitoring Processes.

It is a primary object of the present invention to provide a apparatus and method for detecting and terminating an Sleep Apnea event and Hypopnea episode, within seconds of aid detection. To perform the process I draw your attention to FIG. 5A. FIG. 5A is a block diagram of the Process of Training. The Signals that are generated during Training Periods #1 and #2 are used by the invention to perform Self-checking. This Self-checking procedure verifies that the invention is operating as intended.

The Process of Self-Checking commences when the patient dons the invention and presses button On/Off Switch 401 (not shown in FIG. 5 ). The patient is directed to adjust the Belt 165 (not shown in FIG. 5 ) and Velcro clasp by plain, spoken commands. These spoken commands are fetched from FLASH RAM 406 (not shown in FIG. 5 ) by the Computer 409 (not shown in FIG. 5 ) and broadcast to the patient by Bluetooth wireless 410 (not shown in FIG. 5 ) to the patients Bluetooth Earbud 715 (not shown in FIG. 5 ) and/or the Speaker 411 (not shown in FIG. 5 ). The directions are supplied to the patient to insure that the Integrated Plethysmographics' Shuttle 270 (not shown in FIG. 5 ) is in its' rest position within Guide 275 (not shown in FIG. 5 ) that allows for uninterrupted movement of the Shuttle 270 (not shown in FIG. 5 ) during inspiration and exhalation.

Furthermore, the Signals are Measured to become a set of Referential Parameters (the process that is used to create these Referential Parameters is addressed in detail later in this document).

The Process of Training: During Training Period #1, the patent is directed to breath in specific patterns by plain, spoken commands. These spoken commands are fetched from FLASH RAM 406 (not shown in FIG. 5 ) by the Computer 409 (not showing FIG. 5 ) and broadcast to the patient by Bluetooth wireless 410 (not shown in FIGS. 5 ) to the patients Bluetooth Earbud 715 (not shown in FIG. 5 ) and/or the Speaker 411 (not shown in FIG. 5 ). This Process of Training commences when the patient dons the invention and presses button On/Off Switch 401 (not shown in FIG. 5 ) The specific patterns include but not limited to:

-   -   “Natural Breathing”     -   “Deep Breathing”     -   “Fast Breathing”     -   “Slow Breathing”     -   “No Breathing”     -   “Shallow Breathing”     -   “Breath while Supine”     -   “Breath on the patients Left Side”     -   “Breath on the patients Right Side”     -   “Breath while Prone”

During Training Period #2 the patent is directed to push the Control1 Switch 402 (not shown in FIG. 5 ) as they are preparing to go to sleep.

All Signals are Measured by the Computer 409 (not shown in FIG. 5 ) to derive Values for the Signals intrinsic Parameters. All Signals are Measured and Processed in an identical manner.

To illustrate how Signals are Measured by the Computer 409 (not shown in FIG. 5 ) to derive Values for the Signals' intrinsic Parameters and then Processed we will use the Measurement of a single Parameter as an example. Review FIG. 5A.

For this example, the Signal Parameter that will be Measured and Processed is “Amplitude” 316 (not shown in FIG. 5 ): The “Amplitude” is representative of the expansion of the Thorax or Abdomen that occurs during an inspiration:

-   -   1. Signal Input Storage 501, collects the stream of Signals 303         (not shown in FIG. 5 ), 312 (not shown in FIGS. 5 ), and 313         (not shown in FIG. 5 ) for 60 seconds.     -   2. Within Block 502 the Signals from within Signal Input Storage         501 are Measured. Values are Processed so that only the largest         Value for any Inspiration is kept.         -   a. The method of this specific Processing follows this             format:             -   i. IF Value(Now) is GREATER than or EQUAL to                 Value(Previous) THEN assign Value(Now) to                 Value(Previous).             -   ii. IF Value(Now) is Less than or Equal to                 Value(Previous) THEN store Value(Previous) within Value                 Storage 503 as it is the largest value for this                 Inspiration.     -   3. The stored largest Values within Value Storage 503 form a set         named VS.     -   4. The Values set VS is arithmetically Processed in the         following manner within Block 504         -   a. Calculate the arithmetic average of the Values in the set             VS.         -   b. Subtract each Value in the set from the arithmetic             average.         -   c. Square the deviation of each Value in the set from the             arithmetic average.         -   d. Calculate the arithmetic average of the Squared             deviations.         -   e. Calculate the square root of the arithmetic average of             the Squared deviations.         -   f. The result is the root-mean-square deviation.     -   5. The arithmetic average of the Values in the set VS is stored         as a Referential Parameter in the Training Period 1 and 2         Referential Parameter Storage 505.     -   6. The root-mean-square deviation of the Values in the set VS is         stored as a Referential Parameter in the Training Period 1 and 2         Referential Parameter Storage 505.

The Process of Monitoring: It is a primary object of the present invention to provide an apparatus and method for detecting and terminating a Sleep Apnea event and Hypopnea episode, within seconds of the detection. FIG. 5B is a block diagram of the Process of Monitoring. The Signals Input Flow 506 comprises Signals 303 (not shown in FIG. 5 ), 312 (not shown in FIGS. 5 ), and 313 (not shown in FIG. 5 ).

Signals Input Flow 506 is Measured and Processed by the Computer by Value Assignment 507. The Processing steps are:

-   -   1. Upon the Measurement by the Computer 409 (not shown in FIG. 5         ) a Numeric Value is assigned for each Parameter that is         Measured.     -   2. The Numeric Value is stored in Numeric Value Storage 508.     -   3. Subtraction arithmetic operation 509. Parametric Numeric         Value(Now) minus it's arithmetic average Referential Parameter         equals Result1.

The Numeric value for a Parameter is further Processed by the Computer (not shown in FIG. 5 ) by recalling the Referential Parameters specific to the Parameter that is being Processed at this time.

The Processing consists of a series logic operation by the Computer (not shown in FIG. 5 ). The format of these series of logic operation Performed within Evaluation 510:

-   -   1. If Result1 is equal or Greater than 0 then Do Nothing.     -   2. If Result1 is Less than 0 then         -   a. Subtract Parametric Numeric Value(Now) from each Value             contained within the Value Set of VS.         -   b. If any result of the previous operation (step 2a) is a             positive integer then:             -   I. Divide Result1 by the root-mean square deviation                 Referential Parameters parameter equals Result2.         -   II. If Results2 is Less than 0 then Do Nothing         -   III. If Results2 is Greater than 0 then present Results2 to             the Fuzzy Control System for determination as to whether             Stimulation should be applied.

FIG. 6 is a Block Diagram of the Fuzzy Control System The Detecting and Terminating Process utilizes Fuzzy logic processes. The Fuzzy Control System controls two Processes.

-   -   1. Monitoring     -   2. Stimulation

Fuzzy logic processing is described, for example, in U.S. Pat. No. 7,426,435, issued to GAUTHIER, et al. Sep. 16, 2008, The disclosures of these United States patents are incorporated herein by reference. Another example is NAZERAN, HOMER et al. A Fuzzy Inference System for Detection of Obstructive Sleep Apnea: Proceedings—23^(rd) Annual Conference— IEEE/EMBS Oct.25-28, 2001, Istanbul, TURKEY, which is hereby incorporated by reference.

Referring to FIG. 6 , the Fuzzy Control System Process for Monitoring is as follows:

Result2 values are the input variables to the Fuzzy Control System. The Result2 values are mapped into by sets of membership functions known as “fuzzy sets”. The process of converting a Result2 values (in the nomenclature of Fuzzy Logic these Result2 values are referred to as Crisp Input Values) to a fuzzy value is called “fuzzifi-cation”. The fuzzification” occurs in the Input stage 601 of the Fuzzy Control System. The “fuzzified” Result2 values are evaluated in the next stage of the Fuzzy Control System, the Processing stage 602. The Processing stage 602 uses a collection of logic rules. The Computer then makes decisions for what action to take based on that collection of logic rules. The Rules are in the form of IF statements:

An example of a logic rule would be:

-   -   IF amplitude IS very low AND periodicity IS very long apply         stimulation.

In this example, the two input variables are “very low” and “very long” that have values defined as fuzzy sets. The output variable, “stimulation”, is also defined by a fuzzy set that can have values like “long”, “louder, “less loud”, and so on.

The results of the Processing Stage are combined to give a specific (“Crisp”) answer; this “Crisp” answer translates results into values. This takes place in the Crisp Control Stage 604. If the “Crisp” answer is to initiate Stimulation then the Process steps are as described or shown herein.

FIG. 7 is a diagram of a typical Patient wearing the invention. Patient 700, has the positioned the Housing 705 on his Thorax and has fastened Belt 710 to hold it in place. The patient 700 is wearing the Bluetooth Earbud 715.

FIG. 8 is a Block Diagram of Portrait Development.

Before continuing it may be advantageous to set forth definitions of certain words and phrases.

Stored Portrait Stimulation Parameters are:

-   -   Effective Portraits     -   Irritation Index     -   Audio Portrait     -   Force Portrait     -   Effectivity Index

Effective Portraits:

Is that combination of an Audio Portrait and a Force Portrait that have been found through a Process (described below) to generate an inspiration in a Patient who is having an Sleep Apnea event or Hypopnea episode. Irritation Index:

The Irritation Index is an arbitrary value assigned to Portraits Audio and Force at the time that the Portrait is created and inputted into the FLASH RAM 406. It is indicative of how reactive a patient would be to that Portrait, As an example, the playing of an Audio file of a woman screaming would be assigned a higher Irritation Index value than that of Audio file of a birds singing.

Force Portrait:

The mechanical tactile sensory stimulator 200 (not shown in FIG. 6 ) differ from a simple vibrator in that it is capable of simulating a wide range of tactile effects. The Haptic effects are assembled by using software instructions to control the force amplitude, wave shape, and pulse duration to the stimulation effectors. These instructions are combined to form Force Portraits. The Force Portraits are stored in the Haptic effects library area of the Portrait Storage 801 (not shown in FIG. 6 ). Different Force Portraits are felt as different tactile sensations by the patients. These Force Portraits are assigned an Irritation Index value. The choice of which Force Portrait to use for the mechanical tactile sensory stimulator is determined by the Fuzzy Logic System. Audio Portrait

A method of Stimulation is the playing of prerecorded Audio files. These Audio files are stored in the Portrait Storage 801 (not shown in FIG. 6 ) as Audio Portraits. The Audio Portrait is made up the Audio File Name, a Volume value, the File length, and the Audio File Irritation Index value. There are multiplicities of stored Audio Portrait. The Audio files are sent to the patient by a Bluetooth wireless transmitter 410 (not shown in FIG. 6 ) to a Bluetooth wireless Earbud 715 (not shown in FIG. 6 ). Bluetooth is a wireless protocol utilizing short-range communications technology facilitating data transmission over short distances from fixed and/or mobile device. Bluetooth wireless communication is described, for example, in U.S. Pat. No. 7,225,064, issued to FUDALI, et al. May 29, 2007. The disclosures of these United States patents are incorporated herein by reference. The choice of which Audio Portrait to use for the Audio Stimulus is determined by the

Fuzzy Logic System. Effectivity Index:

The Effectivity Index is the sum of the Irritation Indexes of an Audio and Force Portraits couple. The larger the numerical value of the Effectivity Index than the more vigorous the Stimulus delivered to the patient. The present invention relates to an apparatus to detect and end an occurrence of a Sleep Apnea event or Hypopnea episode, in a manner that will decrease or eliminate hypoxia, hypercapnia and the disturbance of pulmonary hemodynamics.

To apply Stimulus in a manner that will decrease or eliminate hypoxia, hypercapnia and the disturbance of pulmonary hemodynamics it is necessary to determine what stimuli is both effective in initiating Inspiration within 2 seconds of the stimulus application while simultaneously decreasing or eliminating the disturbance of pulmonary hemodynamics.

The Method to develop a set of stimuli that is both effective in initiating Inspiration within 2 seconds of the Stimulus application while simultaneously decreasing or eliminating the disturbance of pulmonary hemodynamics is as follows. The sets of stimuli are called Effective Portraits.

When the Fuzzy Control System Process of FIG. 6 (not shown in FIG. 8 ) detects the onset of a Sleep Apnea event or Hypopnea episode, it attempts to select the of Effective Portrait from within Portrait Storage 801.

If there is no Effective Portrait as would happen when the patient initially dons the invention then the Process of developing an Effective Portrait commences:

-   -   1. The Fuzzy Control System of FIG. 6 (not shown in FIG. 8 )         inputs a random selection of a Force and Audio Portrait from the         Portrait Library 802 forming a Temporary Couple.     -   2. The Temporary Couple is sent to the Stimulus Effectors 806.     -   3. After a 2 Second Delay 805 the Fuzzy Logic System of FIG. 6         (not shown in FIG. 8 ) Monitors the patient to determine if         there is an inspiration.     -   4. If Fuzzy Logic System of FIG. 6 (not shown in FIG. 8 )         determines that further Stimulation is required then another         random selection of a Force and Audio Portrait is made from the         Portrait Library 802 forming another Temporary Couple.     -   5. This Temporary Couple will have a larger Effectivity Index         than the previous Temporary Couple Effectivity Index.     -   6. This Temporary Couple is sent to the Stimulus Effectors 806.     -   7. After a 2 Second Delay 805 the Fuzzy Logic System of FIG. 6         (not shown in FIG. 8 ) Monitors the patient to determine if         there is an inspiration.     -   8. Steps 5-7 cycle until the Fuzzy Logic System of FIG. 6 (not         shown in FIG. 8 ) determines that Stimulus is no longer         required. The Temporary Couple is stored in Portrait Storage 801         as an Effective Portrait.

Effectivity of the Effective Portrait changes in a cyclic pattern during sleep as the amount of Stimulus required to initiate an inhalation waxes and wanes.

This is the Method for adapting to that cyclic process

When the Fuzzy Control System Process of FIG. 6 (not shown in FIG. 8 ) detects the onset of a Sleep Apnea event or Hypopnea episode, it attempts to use the Effective Portrait that has been stored in Portrait Storage 801.

If there is an Effective Portrait in Portrait Storage 801 then the Fuzzy Control System of FIG. 6 (not shown in FIG. 8 ) will:

-   -   1. Send that Effective Portrait to the Stimulus Effectors 806.     -   2. After a 2 Second Delay 805 the Fuzzy Logic System of FIG. 6         (not shown in FIG. 8 ) Monitors the patient. If the Fuzzy Logic         System of FIG. 6 (not shown in FIG. 8 ) determines that further         Stimulation is required-.

a Force and Audio Portrait is chosen from the Portrait Library 802 forming

a Temporary Couple whose Effectivity Index is incrementally greater than the Effectivity Index of the Effective Portrait stored in Portrait Storage 801.

-   -   b. Sends that Effective Portrait to the Stimulus Effectors 806.         -   i. Step 2 cycles until the Fuzzy Logic System of FIG. 6 (not             shown if FIG. 8 ) determines that there exists' no need             further for Stimulation (an inhalation is detected).         -   ii. This Temporary Couple replaces the Effective Portrait             stored within Portrait Storage 801.     -   3. If the Fuzzy Logic System of FIG. 6 (not shown in FIG. 8 )         determines that no further Stimulation is required then when the         next Sleep Apnea event or Hypopnea episode is detected-.         -   a Force and Audio Portrait is chosen from the Portrait             Library 802 forming     -   a Temporary Couple whose Effectivity Index is incrementally less         than the Effectivity Index of the Effective Portrait stored in         Portrait Storage 801.         -   b. Sends that Temporary Couple to the Stimulus Effectors             806.         -   c. After a 2 Second Delay 805 the Fuzzy Logic System of FIG.             6 (not shown in FIG. 8 ) Monitors the patient.             -   i. If the Fuzzy Logic System of FIG. 6 (not shown in                 FIG. 8 ) determines that no further Stimulation is                 required then this Temporary Couple replaces the                 Effective Portrait stored within Portrait Storage 801.             -   ii. If the Fuzzy Logic System of FIG. 6 (not shown in                 FIG. 8 ) determines further Stimulation is required then     -   1) A Force and Audio Portrait is chosen from the Portrait         Library 802 forming a Temporary Couple whose Effectivity Index         is incrementally greater than the Effectivity Index of the         Effective Portrait stored in Portrait Storage 801.     -   2) Sends that Effective Portrait to the Stimulus Effectors 806.     -   3) After a 2 Second Delay 805 the Fuzzy Logic System of FIG. 6         (not shown in FIG. 8 ) Monitors the patient.     -   4) Step 3) cycles until the Fuzzy Logic System of FIG. 6 (not         shown if FIG. 8 ) determines that there exists' no need further         for Stimulation (an inhalation is detected.     -   5) This Temporary Couple replaces the Effective Portrait stored         within Portrait Storage 801. Citation List

PATENT LITERATURE

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Non-Patent Literature

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What is claimed is:
 1. A system for treating a breathing disorder comprising: a sensor capable of detecting physiologic signals; a patient stimulator configured to operate independently of any administration of gases or positive airway pressure; a processor connected to the sensor and the patient stimulator, the processor being configured to process information from the sensor to detect patterns and abnormalities of respiration of a patient, and to determine a physiologic state of the patient; select, in response to the physiologic state of the patient, from a group of stimuli consisting of stationary auditory stimuli and non-stationary auditory stimuli having time-varying frequency content, a first stimulus comprising a stationary auditory stimulus and a second stimulus comprising a non-stationary auditory stimulus having time-varying frequency content; configure, in response to the physiologic state of the patient, attributes of each selected stimulus to elicit a desired physiologic response comprising initiation of inhalation while avoiding or mitigating an undesired physiologic response comprising recruitment of the ascending arousal system and transition from a deeper stage of sleep to a lighter stage of sleep, the attributes including a start timing, an intensity, and a duration; and generate a control signal to cause the stimulator to deliver each selected stimulus in response to detecting a physiologic state that predicts an onset of an apnea or a hypopnea, and to terminate delivery of stimuli immediately upon detection of an inhalation, so that stimuli are not delivered when the patient is breathing normally; wherein the system is configured to operate without any requirement for any clinical assessment, decision-making, determination of parameter values, data entry, or other intervention by a health professional.
 2. The system of claim 1, the processor being further configured to generate a control signal to cause the stimulator to deliver each selected stimulus at a start time synchronized to a physiologic signal detected by the sensor.
 3. The system of claim 1, wherein the processor is further configured to generate a control signal to cause the stimulator to deliver each selected stimulus to elicit initiation of inhalation before airflow has been interrupted for a full 10 seconds, so that the interruption of airflow is less than 10 seconds.
 4. The system of claim 1, wherein the processor is further configured to configure the modifiable attributes and timing of each selected stimulus to prevent habituation.
 5. The system of claim 1, wherein the processor is further configured to configure the attributes of each selected stimulus to avoid or mitigate an additional undesired physiologic response selected from the group consisting of altered cardiac activity, increased systolic blood pressure, and increased circulating catecholamines.
 6. The system of claim 1, wherein the sensor comprises a microphone.
 7. The system of claim 1, wherein the sensor comprises a plethysmograph.
 8. The system of claim 1, wherein the sensor comprises a photodetector.
 9. The system of claim 1, wherein the non-stationary auditory stimuli having time-varying frequency content comprise naturalistic audio signals.
 10. The system of claim 1 wherein the processor is further configured to select, in response to the physiologic state of the patient, an additional stimulus from a group of stimuli consisting of haptic stimuli.
 11. The system of claim 1 wherein the processor is further configured to select, in response to the physiologic state of the patient, an additional stimulus from a group of stimuli consisting of optical stimuli.
 12. A method for treating a breathing disorder comprising: processing information from a sensor capable of detecting physiologic signals to detect patterns and abnormalities of respiration of a patient, and to determine a physiologic state of the patient; selecting, in response to the physiologic state of the patient, from a group of stimuli consisting of stationary auditory stimuli and non-stationary auditory stimuli having time-varying frequency content, a first stimulus comprising a stationary auditory stimulus and a second stimulus comprising a non-stationary auditory stimulus having time-varying frequency content; configuring, in response to the physiologic state of the patient, attributes of each selected stimulus to elicit a desired physiologic response comprising initiation of inhalation while avoiding or mitigating an undesired physiologic response comprising recruitment of the ascending arousal system and transition from a deeper stage of sleep to a lighter stage of sleep, the attributes including-a start timing, an intensity, and a duration; delivering, independent of any administration of gases or positive airway pressure, each selected stimulus to the patient using the patient stimulator in response to detecting a physiologic state that predicts an onset of an apnea or a hypopnea, and terminating delivery of stimuli immediately upon detection of inhalation, so that stimuli are not delivered when the patient is breathing normally; and operating without any requirement for any clinical assessment, decision-making, determination of parameter values, data entry, or other intervention by a health professional.
 13. The method of claim 12, wherein each selected stimulus is delivered at a time synchronized to a physiologic signal detected by the sensor.
 14. The method of claim 12, wherein a physiologic state is detected that predicts onset of an apnea or hypopnea and each selected stimulus is delivered to elicit initiation of inhalation before airflow has been interrupted for a full 10 seconds, so that the interruption of airflow is less than seconds.
 15. The method of claim 12, wherein the attributes and timing of each selected stimulus are chosen to prevent habituation.
 16. The method of claim 12, wherein the steps of the method are performed while the patient is using a Positive Airway Pressure machine.
 17. The method of claim 12, wherein the attributes of each selected stimulus are further configured to avoid an additional undesired physiologic response selected from the group consisting of altered cardiac activity, increased systolic blood pressure, and increased circulating catecholamines.
 18. The method of claim 12, wherein the sensor comprises a microphone.
 19. The method of claim 12, wherein an additional stimulus is selected, in response to the physiologic state of the patient, from a group of stimuli consisting of haptic stimuli.
 20. The method of claim 12, wherein an additional stimulus is selected, in response to the physiologic state of the patient, from a group of stimuli consisting of optical stimuli. 